Music recommendation systems and services such as Pandora, Ringo and Spotify are becoming an increasingly popular way for users to find and listen to music that may be of interest to them. Most of these music recommendation systems identify music for the user to listen to based on the user's personal preferences as indicated by the user through manual selection or some other type of affirmative user action indicating the user's preferences (e.g., “like”).
Pandora is free personalized internet radio. The service plays musical selections of a certain genre based on the user's artist selection. The user then provides positive or negative feedback for songs chosen by the service, which are taken into account when Pandora selects or recommends future songs to the user.
Pandora recommends songs based on a certain genre and artist that the user has selected in advanced. Furthermore, the user needs to provide positive or negative feedback for songs chosen by the service, which are taken into account when Pandora selects future songs to further improve the music recommendation system.
Ringo is a music recommendation system accessible to users only via email. Users rate musical artists and then are able to receive recommendations for further listening.
Spotify is a new way to enjoy music socially. Spotify does not recommend songs based on individual preferences, but instead allows registered users to integrate their account with existing Facebook and Twitter accounts. Once a user integrates their Spotify account with other social media profiles, they are able to access their friends' favorite music and playlists. Because music is social, Spotify allows you to share songs and playlists with friends, and even work together on collaborative playlists.
However, existing music recommendation systems and services such as the above are relatively inflexible in that they generally do not take into account the changing music preferences of users of mobile devices (e.g., smartphones) from moment to moment as they engage in different activities or enter different environments. Mobile device users typically use their devices on the go while engaged in various different activities and located in environments in which their music listening preferences may change from moment to moment. Requiring users to manually set or change their personal music listening preferences on their mobile device can be inconvenient as they are constantly changing between different activities or environments, especially considering the limited user interface currently provided by mobile devices.
In view of the above, there is a need for a music recommendation system and service for users of mobile devices such as smartphones that better takes the changing music preferences of the user into account.